Generative AI coding tools and agents do not work for me

Great article. The other thing that you miss out on when you don't write the code yourself is that sense of your subconscious working for you. Writing code has a side benefit of developing a really strong mental model of a problem, that kinda gets embedded in your neurons and pays dividends down the track, when doing stuff like troubleshooting or deciding on how to integrate a new feature. You even find yourself solving problems in your sleep.

I haven't observed any software developers operating at even a slight multiplier from the pre-LLM days at the organisations I've worked at. I think people are getting addicted to not having to expend brain energy to solve problems, and they're mistaking that for productivity.

> I think people are getting addicted to not having to expend brain energy to solve problems, and they're mistaking that for productivity.

I think that's a really elegant way to put it. Google Research tried to measure LLM impacts on productivity in 2024 [1]. They gave their subjects an exam and assigned them different resources (a book versus an LLM). They found that the LLM users actually took more time to finish than those who used a book, and that only novices on the subject material actually improved their scores when using an LLM.

But the participants also perceived that they were more accurate and efficient using the LLM, when that was not the case. The researchers suggested that it was due to "reduced cognitive load" - asking an LLM something is easy and mostly passive. Searching through a book is active and can feel more tiresome. Like you said: people are getting addicted to not having to expend brain energy to solve problems, and mistaking that for productivity.

[1] https://storage.googleapis.com/gweb-research2023-media/pubto...

You’re twisting results. Just because they took more time doesn’t mean their productivity went down. On the contrary, if you can perform expert task with much less mental resources (which 99% of orgs should prioritize for) then it is an absolute win. Work is extremely mentally draining and soul crushing experience for majority of people, if AI can lower that while maintaining roughly same result with subjects allocating only, say, 25% of their mental energy – that’s an amazing win.

If I follow what you are saying, employers won't see any benefits, but employees, while they will take the same time and create the same output in the same amount of time, will be able to do so at a reduced mental strain?

Personally, I don't know if this is always a win, mostly because I enjoy the creative and problem solving aspect of coding, and reducing that to something that is more about prompting, correcting, and mentoring an AI agent doesn't bring me the same satisfaction and joy.

And how long have you been doing this? Because that sounds naive.

After doing programming for a decade or two, the actual act of programming is not enough to be ”creative problem solving”, it’s the domain and set of problems you get to apply it to that need to be interesting.

>90% of programming tasks at a company are usually reimplementing things and algorithms that have been done a thousand times before by others, and you’ve done something similar a dozen times. Nothing interesting there. That is exactly what should and can now be automated (to some extent).

In fact solving problems creatively to keep yourself interested, when the problem itself is boring is how you get code that sucks to maintain for the next guy. You should usually be doing the most clear and boring implementation possible. Which is not what ”I love coding” -people usually do (I’m definitely guilty).

To be honest this is why I went back to get a PhD, ”just coding” stuff got boring after a few years of doing it for a living. Now it feels like I’m just doing hobby projects again, because I work exactly on what I think could be interesting for others.